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Tumor-intrinsic CD74 expression mediates immune evasion in lung cancer with COPD

GSE194070 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2024/08/15 Platform GPL18573
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Lung cancerThis series is part of our curated briefing on it.
Samples
16 samples: 4 × Control vs 4 × COPD vs 4 × CTumo vs 4 × TumoGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Single-cell transcriptome analysis deciphers the CD74-mediated immune evasion and tumour growth in lung squamous cell carcinoma with chronic obstructive pulmonary diseaseClinical and translational medicine · 2024
Summary (written by the submitters)
To better elucidate the complex interaction between COPD and NSCLC, we comprehensively characterized immune cell dynamics and transcriptome profiles of malignant cells in tumor tissues from NSCLC patients with COPD using single-cell RNA sequencing (scRNA-seq). We observed increased fractions of exhausted CD8+ T cells, CCL18+ tumor-associated macrophages (TAMs), and LAMP3+ dendritic cells (DCs) in the immune component of NSCLC with COPD compared with the findings in NSCLC without COPD.
Read the full summary ↓
Remarkably, a critical cluster of malignant cells from NSCLC with COPD samples, characterized by high expression of CD74, significantly exhibited an epithelial-immune dual signature and was associated with poor prognosis. Interestingly, we found that CD74 facilitated phosphorylation of MAPK/STAT3 to mediate PD-L1 expression and further suppressed CD8+ T cell function, triggering LC progression. Our study provides a comprehensive profiling of the multi-cellular ecosystem of NSCLC with coexisting COPD and reveals that CD74+ cancer cells are potential targets for immunotherapy.
Published in
Single-cell transcriptome analysis deciphers the CD74-mediated immune evasion and tumour growth in lung squamous cell carcinoma with chronic obstructive pulmonary disease
Wang D, Li S, Yang Z et al. · Clinical and translational medicine 2024 · PMID 39113235 · doi:10.1002/ctm2.1786
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE194070_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA798965 and SRA study SRP355995. Searching any of these in the dataset finder brings you back here.

Study design
4 × Control vs 4 × COPD vs 4 × CTumo vs 4 × Tumo

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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